Image acquisition, processing, and display

ABSTRACT

Image data is acquired, processed, and/or displayed in accordance with an embodiment of the present disclosure to display, monitor, and/or demonstrate the progress of an experiment substantially in real-time and with high sensitivity. In one embodiment, at least one time-resolved value of spatially distributed polarization change data is provided and displayed. Advantageously, real-time processing and display of data is provided such that discussion and collaboration about the experiment may occur, time-resolved data is not lost, and resources are not wasted.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 11/321,168 filed on Dec. 29, 2005, which is acontinuation-in-part of U.S. patent application Ser. No. 09/838,700filed on Apr. 19, 2001, which is a continuation-in-part of U.S. patentapplication Ser. No. 09/614,503, filed on Jul. 11, 2000, now U.S. Pat.No. 6,594,011, the full disclosures of which are incorporated byreference herein for all purposes.

This application is related to U.S. patent application Ser. No.10/847,754 filed on May 17, 2004, U.S. patent application Ser. No.10/847,736 filed on May 17, 2004, U.S. patent application Ser. No.10/841,988 filed on May 7, 2004, and U.S. patent application Ser. No.10/046,620 filed on Jan. 12, 2002. The above-mentioned U.S. patentapplication Ser. Nos. 10/847,754, 10/847,736, 10/841,988, and 10/046,620are incorporated by reference herein for all purposes.

BACKGROUND

1. Field of Invention

This invention relates to acquisition and processing of data and moreparticularly to acquisition and processing of microarray data fordisplaying, monitoring, and/or demonstrating the progress of anexperiment substantially in real-time.

2. Discussion of the Related Art

The formation of an array of biologically or chemically active spots onthe surface of a substrate for identifying constituents in test materialbrought into contact with the array is known, such as with a biochip(also referred to as a gene chip, protein chip, microarray, and others).Typically, such processes require spots of, for example,oligonucleotides, cloned DNA, antibodies, peptides, receptors, enzymes,and/or inhibitors, which are processed to exhibit characteristics suchas fluorescence, electroluminescence, current change, and/or voltagechange, for providing a detectable signature for the presence ofconstituents in the material being tested.

Typically, microarray experiments have been analyzed at or near theapproximate endpoint of reactions, which is presumed to be equilibrium,and real-time and/or time-resolved information have not been provided.Disadvantageously, such endpoint analysis does not allow for monitoringof or collaboration about the process under investigation, thus losingkinetic data, affinity data, and other time-resolved data regarding theprocess. Such endpoint analysis also does not allow for modification orearly termination of the experiment if an error occurs, thus wastingtime and resources.

Thus, there is a need for a method and apparatus to gather, process, anddisplay image data which is highly sensitive and substantially atreal-time and/or time-resolved.

SUMMARY

Image data is acquired and processed in accordance with an embodiment ofthe present invention to display, monitor, and/or demonstrate theprogress of an experiment substantially in real-time and with highsensitivity. Advantageously, the present invention allows for real-timeprocessing and display of data such that discussion and collaborationabout the experiment may occur, time-resolved data is not lost, andresources are not wasted.

In accordance with one embodiment of the present invention, an imageprocessor is provided, including a data acquisition application adaptedto receive spatially distributed polarization change data caused by aspecimen array; and a data analyzer operably coupled to the dataacquisition application, the data analyzer adapted to calculate at leastone time-resolved value of the spatially distributed polarization changedata.

In accordance with another embodiment of the present invention, anapparatus for imaging is provided, including a light source emitting apolarized light beam; an optical assembly including a light reflectionsurface, wherein the light beam from the light source is reflected bythe light reflection surface to provide an evanescent field adjacent thelight reflection surface, the light reflection surface being adapted toallow placing thereon a specimen array such that the specimen array inthe evanescent field causes spatially distributed polarization changesin the cross-section of the light beam; and a two-dimensional arraydetector positioned to detect the spatially distributed polarizationchanges caused by the specimen array. A processor is operably coupled tothe two-dimensional array detector, the processor processing data fromthe two-dimensional array detector to provide a two-dimensionalrepresentation of the spatially distributed polarization changesoccurring in the specimen array in real-time.

In accordance with yet another embodiment of the present invention, amethod of processing image data is provided, including receivingspatially distributed polarization change data caused by a specimenarray; and calculating at least one time-resolved value of the spatiallydistributed polarization change data.

In accordance with yet another embodiment of the present invention, amethod of imaging is provided, including passing a polarized light beaminto an optical assembly including a control layer and a lightreflection surface to provide an evanescent field with controlled heightand intensity adjacent the light reflection surface, a specimen array inthe evanescent field causing spatially distributed polarization changesin the cross-section of the light beam; passing the reflected light beamout of the optical structure; and detecting the spatially distributedpolarization changes caused by the specimen array. The method furtherincludes processing the detected spatially distributed polarizationchanges to provide a two-dimensional representation of the spatiallydistributed polarization changes occurring in the specimen array inreal-time.

The scope of the invention is defined by the claims, which areincorporated into this section by reference. A more completeunderstanding of embodiments of the present invention will be affordedto those skilled in the art, as well as a realization of additionaladvantages thereof, by a consideration of the following detaileddescription of one or more embodiments. Reference will be made to theappended sheets of drawings that will first be described briefly.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram of an illustrative system in accordance withan embodiment of the present invention;

FIG. 2 is a block diagram of an embodiment of the system of FIG. 1;

FIG. 3 is a block diagram of a processor in accordance with anembodiment of the present invention;

FIG. 4 is a block diagram of image measurements in accordance with anembodiment of the present invention;

FIG. 5 is a block diagram of parameter inputs in accordance with anembodiment of the present invention;

FIG. 6 is a block diagram of a measurement module of an imaging methodin accordance with an embodiment of the present invention;

FIG. 7 is a block diagram of a modeling module of an imaging method inaccordance with an embodiment of the present invention;

FIG. 8 is a block diagram of a data handling method in accordance withan embodiment of the present invention;

FIG. 9 is a block diagram of an image data analysis method in accordancewith an embodiment of the present invention;

FIG. 10 is a block diagram of an image data display method in accordancewith an embodiment of the present invention;

FIG. 11 is a block diagram of coordinate inversion of an image slide inaccordance with an embodiment of the present invention;

FIG. 12 is a block diagram of outputs in accordance with an embodimentof the present invention;

FIG. 13 is a graph of specimen spot intensity over time;

FIG. 14 is a display of a frame of time-resolved specimen spotintensity;

FIG. 15 illustrates a TIFF image of time-resolved specimen spotintensity at a first time;

FIG. 16 illustrates a TIFF image of time-resolved specimen spotintensity at a second time;

FIG. 17 illustrates a differential TIFF image between the images shownin FIGS. 15 and 16; and

FIGS. 18 and 19 are histograms of the TIFF images shown in FIGS. 16 and17.

Embodiments of the present invention and their advantages are bestunderstood by referring to the detailed description that follows. Itshould be appreciated that like reference numerals are used to identifylike elements illustrated in one or more of the figures. It should alsobe appreciated that the figures may not be necessarily drawn to scale.

DETAILED DESCRIPTION

The invention generally comprises a method and apparatus for acquiring,processing, and displaying data, and in one embodiment relates toacquiring, processing, and display of data from a two-dimensionalarrangement of chemical substances obtained by an imaging technique andapparatus, such as that disclosed in U.S. Pat. No. 6,594,011, thecontents of which have been previously incorporated by reference.

In one embodiment, a polarized light source of known polarization stateis directed into an optical assembly, for example a total internalreflection member (TIR member), configured for a reflection at a lightreflection surface, for example a total internal reflection surface (TIRsurface), and then allowed to exit the optical assembly. In the contextof this document, superposition of reflections as encountered at alayered optical structure where the layer thicknesses are smaller thanthe coherence length of the illuminating light is referred to as asingle reflection.

The chemical specimen is in place above the light reflection surface inthe evanescent field of the reflected light beam. After reflection, thebeam is passed to a polarization-sensitive two-dimensional detector suchas a polarizer and a camera or other types of detectors. The beam'scontent can then be processed to determine the change in polarizationstate, locally in the two-dimensional cross-section of the beam. Thisprovides a spatially distributed map of change of polarization state inthe specimen. A variety of techniques are available to determine thechange in polarization such as measuring the deviation from a nullcondition or by comparing the input polarization state to the outputpolarization state.

The refractive index composition of the materials within the evanescentfield determines the change in the polarization state of the beam due tothe reflection at the light reflection surface. A two-dimensionalvariation of this composition within the light reflection surface isassociated with a respective variation of the polarization statespatially distributed across the cross-section of the reflected lightbeam.

In one application, the chemical specimen forms a two-dimensional arrayof molecules (referred to herein as receptors and generally referred toas capture agents or affinity agents) with specific affinities towardsrespective other molecules (referred to herein as ligands). In thisapplication, the invention is utilized to indicate the presence orabsence or rate of binding between ligands and receptors on the array.Such arrays commonly consist of a plurality of discrete specimen spots.The present method and apparatus images the array so as to distinguisheach of the discrete specimen spots represented by the local change inpolarization state in the cross-section of the reflected beam.

Measurements are designed for maximum practical sensitivity andtriggered at discrete intervals appropriate for the experiment,determined by a three-component analysis based on the affinityconstants, size, and concentration of the analytes. Data is culled forconservation of computing and storage resources. If, for instance, it isknown that the sample system contains low-affinity components, generallylonger incubation or dwell time is required. If size of the analyte issmall, maximum sensitivity settings of the instrument are required whichin turn generally requires longer measurements and correspondinglylonger intervals. If the concentration is low, such that a longincubation or dwell time is required, measurements will be timedaccordingly so that excess data is not taken. If the reaction involveshigh affinity components, measurement intervals will be minimized, sothat more data points are taken. Incubation and dwell time refer to theperiod of time in which the sample is in contact with the sensing arrayat nearly full concentration.

If the characteristics of the sample are unknown, an auto-tuning anddata culling method is employed, in which binned low-spatial-resolutiondata is taken at moderate sensitivity settings and minimized intervals,the resultant differential images are analyzed for change, and oncesignals become evident or fail to become evident in a given time period,kinetic analyses of reactive areas are used to adjust measurementintervals, sensitivity, and spatial resolution to appropriate levels,while the data that displays no differential is discarded except for afew measurements, such as every fifth, tenth. If, for instance, thereaction becomes evident in the first ten seconds of incubation,measurement will proceed at maximal speed and moderate sensitivity forthe duration, binning will continue to be employed and all data will besaved.

FIGS. 1 and 2 show an apparatus which implements one embodiment of theinvention. As shown in FIG. 1, the apparatus 10 can be describedconveniently as comprising three general portions. A first portionincludes a polarized light source assembly 12, a second portion includesan optical assembly 14 providing a control layer and/or a lightreflection surface, and a third portion includes apolarization-sensitive imaging detector assembly 16 which can employ forexample a two-dimensional array detector.

Data from detector assembly 16 is sent by an electrical signal along aconnector 24 to processor 18 such as a specially programmed computer anduser access system including an image display. Data can be presented asan image, a data table, a graph, or in other forms. The polarized lightsource assembly 12 passes polarized light of known polarization state20, which may be varied or varying to optical assembly 14 where a lightbeam reflection occurs. Reflected light 22, having a changedpolarization state, passes to detector assembly 16, where it is recordedspatially over the cross-section of the beam. The recorded data is sentto processor 18 where the change of polarization state is determined toprovide a spatially resolved map of changes in polarization state. Wherethe specimens are presented as an array of discrete spots, each spotwill be imaged for its change in polarization state within the spotarea.

FIG. 2 shows a more detailed schematic block diagram of one embodimentof apparatus 10. The polarized light source assembly 12 has a lightsource 26, a beam forming member 28 (if the nature of the light sourceis such as to make beam forming useful or necessary), a polarizer 30,and an optical retarder 32. In other embodiments, the light source mayinclude a laser and a moving diffuser adapted to producespeckle-offsetting fluctuation of the minima and maxima in the specklepattern caused by the laser. The moving diffuser may be attached to amechanical actuator which is preferably a motor and servo-apparatus forproviding the speckle offsetting fluctuations. The light beam thenproceeds through the beam-forming element 28, the polarizer 30, and theoptical retarder 32, exiting light source assembly 12 as light beam 20.

In this embodiment, the optical assembly 14 has an optical element 34which has an optical surface 36. Also shown is a control layer 38 overoptical surface 36, and between them an index matching substance 40. Aspecimen 42 is positioned on light reflection surface 39 of controllayer 38 in one example. In an alternative optical arrangement, acontrol layer is placed above an index matching substance which in turnis placed above a flat optical member. However constructed, theinvention incorporates an optical structure having a light reflectionsurface and the beam reflects at the reflection surface between enteringand leaving the optical structure. In other words, there is a lightreflection surface in optical contact with the specimen, such that theevanescent field associated with the total internal reflection interactswith the specimen.

In one embodiment, the post-reflection detector assembly 16 has apolarizer 44 and an imaging detector, for example a two-dimensionalarray detector 46 and preferably a camera of the CCD or CMOS array type.The post-reflection detector assembly 16 through which the beam 22passes can alternatively consist of a polarizer member, a beam formingmember, and an imaging detector such as a two dimensional array detectoror other type of imaging detector.

The processor 18 is a specially programmed computer (or processor) andoutput means for processing the imagery into a representation of filmthickness variations spatially resolved over the cross-section of thearea imaged. The imaging is acquired by detecting changes spatiallydistributed in the local polarization state in the beam's cross-sectioncaused by the total internal reflection. This provides information aboutthe presence and composition in the array of substances on the substratesurface for each resolvable point on the surface. Different polarizationstate changes are included in the cross-section of the reflected beamindicative of the substances on the specimen in the location in thespecimen array corresponding to a position in the detector.

Processor 18 receives the data as an electrical signal (on connector 24)and characterizes the change of polarization state spatially over thetwo-dimensional array. In processor 18, the analysis and processing isdone in one embodiment by comparing the known polarization state of theincoming light from the light source assembly 12 with the changedpolarization state of the reflected light 22, spatially resolvedtwo-dimensionally within the beam which provides a map of spatiallydistributed points or spots in the specimen array. The polarizationshift is then analyzed by processor 18 to provide information of thepresence and properties of elements in the chemical specimen. Otherknown techniques, such as null processing can be used to determine thechange in polarization state.

The processor can be a general or special purpose processor, preferablywith network capabilities. It comprises a central processing unit (CPU),a memory, and a network adapter, which are interconnected by a main bus.Other conventional means, such as a display, a keyboard, a printer, abulk storage device, and a read-only memory (ROM), may also be connectedto the main bus. The memory may store network and telecommunicationsprograms and an operating system (OS).

The invention as described above provides an extremely sensitive opticalimaging system for real-time imaging of the binding status of biochiparray elements on the surface of an optically transparent material suchas a glass or plastic chip. An exemplary monitored array of a 15 mmsquare inscribed in a 20 mm circular field, with discrete specimen spotsof size commensurate with the lateral resolution of the imaging optics,results in fully parallel, continuous real-time readout of up to 5million sensor fields. Sensor sensitivity to surface attachment is inthe femtogram/mm.sup.2 range (e.g., one DNA per square micron).

The apparatus of FIG. 1 operates by imaging the pattern of reactions onthe biochip. Those reactions produce changes in the height, surfaceconcentration, and/or refractive index of the material that reacts ateach spot. The area imaged could be the entire biochip array or aportion of the entire biochip array. By providing an array of spots ofdifferent materials, different constituents in test material flowed overthe spots bind in a manner which identifies those constituents. Byincluding in a computer memory the positions of the various materials inthe different spots of the array, the image produced by the apparatus ofFIG. 1 identifies the constituents in the test material and can alsodetermine the rate at which the reactions occur by imaging successivelyover time. With the apparatus described, height differences can beimaged dynamically over such short periods of time that intermediateheight change readings can be recorded and therefore height change ratescan be determined as well as allowing comparison of the rate of heightchange or intermediate amount of height change among the spots on thebiochip array.

The processing and display of the image data by processor 18 will now bediscussed in greater detail.

Typically, microarray experiments have been analyzed at or near theapproximate endpoint of reactions, which is presumed to be equilibrium,and have not provided real-time and/or time-resolved information.Endpoint analysis shows whether the experiment has worked or not butdoes not provide a way for real-time analysis and time-resolvedanalysis. Disadvantageously, such endpoint analysis does not allow formonitoring of the process under investigation, thus losing kinetic data,affinity data, and other time-resolved data regarding the process. Forexample, the present invention allows for the detection of time-relatedaffinity data if certain molecules bind to a part of the array at thebeginning of an experiment but the binding does not persist until theend of the experiment. Disadvantageously, endpoint analysis would notcapture this type of data.

Such endpoint analysis also does not allow for modification or earlytermination of the experiment if an error occurs, thus wasting time andresources. For example, the present invention allows a user to changecertain parameters to focus on an area of the array after viewing theprogress of the experiments if so desired. Positive controls may beobserved to verify that the chemistry and detection is working. Inanother example, if an air bubble or other system failure were to arisein the experiments and cause a significant error in the imaging or ifthe chemistry itself was to fail, the present invention's real-timeand/or time-resolved imaging and display allows the user to stop theprocess and restart or modify the experiments or to correct the systemfailure. An endpoint analysis after full preparation and completion ofthe experimental process would be a waste of the precursor materials,money, time, and other experimental resources.

As noted above, in one embodiment, processor 18 includes a speciallyprogrammed computer (or processor) and display means for processing theimage data in real-time into a representation of film thicknessvariations time-resolved and spatially-resolved over the cross-sectionof the area imaged.

FIG. 3 illustrates one embodiment of processor 18, which includes a dataacquisition application 80 operably coupled to a data analysisapplication 82 which in turn is operably coupled to a data displayapplication 85. Processor 18 further includes a parameter inputinterface 90 which is operably coupled to data analysis application 82.A browser 87 operably couples data display application 85 to acommunication network, for example the Internet. A display device 89 isoperably coupled to data display application 85 for displaying thegraphical representations of the image data to a viewer. Both browser 87and display device 89 are commercially available and known to those ofordinary skill in the art.

The image data may be presented in a hypertext markup language (HTML)format or any similar or succeeding similar language such as PHP:Hypertext Preprocessor (PHP), Active Server Pages, or Perl. This allowsfor ease of communication and sharing of the image display at remotelocations through the Internet or other networking means via variousdisplay devices, such as PC display screens, personal digital assistants(PDAs), wireless telephones, and other mobile devices, as well asdisplay near or proximate data acquisition application 80 as shown bydashed line 83.

Data from detector assembly 16 (FIG. 1) is sent along connector 24 inreal-time and acquired by data acquisition application 80. The dataoutputted from data acquisition application 80 is sent along line 81 todata analysis application 82, where the data for multiple microarrayspots is analyzed and normalized to quantify an intensity value andcorresponding thickness value in real-time and over time (i.e., the datais time-resolved).

Output data from data analysis application 82 is sent along line 84 todata display application 85 which converts the output data intographical representations for the viewer. In one embodiment, theintensity value is posted in a grid that represents the microarrayitself and allows for display of the grid development in real-time andover time as will be explained in greater detail below.

Most microarray experiments include positive controls, negativecontrols, and/or dilutions over certain areas of the grid. Negativecontrols should not react during the experiments and are used todetermine the background or baseline for the intensity measurements.Theoretically, positive controls and/or dilutions should producereactions during the experiments and are therefore the brightest (ordarkest depending on the display convention) areas of the image.Typically, positive controls on microarrays are set at the margins orother easily located positions, so that they may be used to determine aframe of reference or establish a reference direction, correct imageaberration and distortion, or accomplish registration of images to becompared. According to an embodiment of the present invention, manycontrols are utilized so as to evaluate spot-to-spot variance.Advantageously, the present invention allows for instant feedback on theprogress of a large number of experiments, ranging from 1 spot to about50,000 spots, as real-time and time-resolved information about themicroarray can be on display.

Data acquisition application 80 receives the image data from detectorassembly 16 (FIG. 1) and can be used to not only receive the image databut to also run the imaging apparatus in one embodiment. In one example,with no intent to limit the invention thereby, data acquisitionapplication 80 can comprise the software package IGOR commerciallyavailable from WaveMetrics, Inc. of Lake Oswego, Oreg., appropriatelymodified to be integrated with at least light source assembly 12 (FIG.1), optical assembly 14 (FIG. 1), detector assembly 16 (FIG. 1), anddata analysis application 82, for automatic data collection andretrieval.

FIG. 4 is a block diagram of an example of image measurements that maybe collected and processed by data acquisition application 80 (FIG. 3)and sent to data analysis application 82 (FIG. 3) along line 81. Dataacquisition application 80 receives raw images 101 taken atpredetermined and/or user-selected time intervals “t_(n)” and provideshorizontal pixel location/coordinate “x”, vertical pixellocation/coordinate “y”, and an intensity value “z” at the pixelcoordinates x and y.

In one embodiment, ellipsometry analysis routines in data acquisitionapplication 80 extract intensity values from the four images 102, 103,104, and 105 at different polarizer positions (in phase modulation mode)and from these four reading determine the ellipsometric x and y valuefor each pixel in the image. This data is then fitted to a lookup tablebased on a selected optical model which results in a thickness map ofx,y coordinates and thickness z.

In another embodiment, if nulling or off-null is used, the intensity mapof an image at a fixed polarizer position (e.g., “direct” settings arein the IGOR control panel and allow these to be set) is fitted to aJones or Mueller matrix optical model and a thickness map is generated.The unpolarized image is one of the four images used to generate x,ycoordinates and is useful as a demonstration of the imbeddedreflectometry measurement capabilities.

Referring back to FIG. 3, data acquisition application 80 outputs imagedata x, y, and z along line 81 to data analysis application 82 whichthen analyzes the image data substantially in real-time to producespatially-resolved images in real-time and over time. Data analysisapplication 82 is able to evaluate and quantify values inside andoutside of each spot in the array. In one example, at predetermined timeintervals, the mean value of a spot and a local background value areselected as the parameters used to approximate an intensity value and acorresponding approximation of thickness over a spot normalized againstaberrations such as drift and local noise. Thus, data analysisapplication 82 is able to quantify and qualify the microarray data fromdata acquisition application 80. In one example, with no intent to limitthe invention thereby, data analysis application 82 can be the softwarepackage ImaGene commercially available from BioDiscovery, Inc. of ElSegundo, Calif., appropriately modified to be integrated at least withdata acquisition application 80, parameter input interface 90, and datadisplay application 85 for data retrieval, analysis, and imageprocessing.

Parameter input interface 90 is used to input parameters into dataanalysis application 82 via line 91. FIG. 5 is a block diagram of anexample of parameter values that may be inputted into data analysisapplication 82 from parameter input interface 90 via line 91.

As shown in FIG. 5, parameters may be inputted for the followingalthough not limited thereto: a physical model 110, a spot templateconstruction 112, an optical model 116, assay conditions 114, and athickness lookup table 118. Parameters for physical model 110 includebut are not limited to the length, width, height, density, orientation,hydrophilicity profile, and affinity profile of the array. Parametersfor spot template construction 112 include but are not limited to thenumber of subarrays, rows and columns, and spot identification.Parameters for optical model 116 include but are not limited towavelength, angle, ambient refractive index (n) and extinctioncoefficient (k), layer of interest n and k, and media n and k.Parameters for assay conditions 114 include but are not limited to themedia type, sample handling, temperature profiling, pump rate profiling,and measurement profile.

Referring now to FIG. 6, a block diagram is shown illustrating anexample of a measurement module 120 of an imaging method that can beutilized by data acquisition application 80 and data analysisapplication 82. In step 121, six frames (a frame is a single still imagefrom a dynamic series) per measurement are taken over timecourse t₀ tot_(final). The raw data is processed in step 122 using ellipsometrycalculations to calculate measured ellipsometric X values and measuredellipsometric Y values 123 and 124, respectively. The raw data alsoincludes measured intensity values in step 125. Reference frames aredesignated and averaged in step 126 and then subtracted from themeasurement frames in step 127. The final frame or the framedemonstrating the most change from the initial frame is processed instep 128 to flag spots which are oversized, undersized, anddonut-shaped.

FIG. 7 is a block diagram illustrating an example of a modeling module130 of an imaging method that can be utilized by data analysisapplication 82. Parameters to be entered for the physical model 131, forexample a biolayer model, include but are not limited to the geometry(from molecular models, crystal structure), orientation, andmulti-segment optical density assignment. Parameters for the opticalmodel 132 include the n, k, and depth of ambient, substrate, functionallayer, biolayer, and media. Wavelength and angle(s) of the light sourceis also entered. These modeling parameters are fit into a BeagleholeMultilayer Model 133 and/or an Evanescent Model 134. A lookup table 135is created including ellipsometric x and y values versus thickness ofthe biolayer based upon the Beaglehole Multilayer Model. A lookup table136 is also created including intensity versus thickness of the biolayerbased upon the Evanescent Model.

FIG. 8 is a block diagram of an example of a data handling method 140that can be utilized by data analysis application 82. A differentialimage is provided by subtracting a reference image (t₀) from the latest(current) image (t_(n)) in step 141. Such a differential image canadvantageously show change with high resolution in real-time to a viewerwhen the image is displayed (see, e.g., FIGS. 15-17). A spot is thenquantified in step 142 by various parameters including but not limitedto a spot mean, median, and mode (MMM), a local background MMM, a spotsize, and a spot qualitative score. The local background is thensubtracted from the spot value in step 143. The spot value is thennormalized to the background and the positive controls in step 144, thuscontrolling for drift noise or other experimental fluctuations. Finally,an affinity analysis may be conducted based upon the normalized spotvalue in step 145.

Table 1 below shows a table including possible output from data analysisapplication 82 but the present invention is not limited to such a list.

TABLE 1 Output Definition Field Name of a field where the spot islocated Metarow Number of metarow in the metagrid where the spot islocated Metacolumn Number of metacolumn in the metagrid where the spotis located Row Number of row in the subgrid where the spot is locatedColumn Number of column in the subgrid where the spot is located GeneIDGene ID information for the spot Flag Numeric code of the quality flagfor the spot (0 - no flag, flag codes 1, . . . , 7) Signal Mean Pixelintensity averaged over the local signal region Background Mean Pixelintensity averaged over the local background region Signal Median Medianpixel intensity computed over the local signal region Background MedianMedian pixel intensity computed over the local background region SignalMode Mode pixel intensity computed over the local signal region (modecorresponds to the pick location in intensity distribution) BackgroundMode Mode pixel intensity computed over the local background regionSignal Area Number of pixels in the local signal region Background AreaNumber of pixels in the local background region Signal Total Total pixelintensity summed over the local signal region Background Total Totalpixel intensity summed over the local background region Signal StdevStandard deviation of pixel intensities over the local signal regionBackground Stdev Standard deviation of pixel intensities over the localbackground region Shape Regularity First signal area of a spot isinscribed into a circle. Than number of non-signal pixels that fallwithin this circle is computed and divided by circle's area. This ratiois subtracted from 1 and is called “shape regularity” Ignored Area Areaof ignored regions directly neighboring (“touching”) the signal area iscomputed Spot Area Signal Area plus Ignored Area Ignored Median Medianpixel intensity computed over the local ignored region Area To PerimeterThis quality measure defines spot's circularity. Area of a spot isdivided by a square of spot perimeter and multiplied by π4. As a result,this measure ranges from 0 (highly non-circular shape) to 1 (a perfectcircle) Open Perimeter Computes the proportion of signal perimeter thattouches the border of rectangular snip around the spot XCoord Xcoordinate (in pixels) of grid circle corresponding to the spot YCoord Ycoordinate (in pixels) of grid circle corresponding to the spot DiameterDiameter (in pixels) of grid circle corresponding to the spot PositionOffset Offset (in pixels) of the center of the grid circle from theexpected position in the grid Offset X X offset (in pixels) of thecenter of the grid circle from the expected position in the grid OffsetY Y offset (in pixels) of the center of the grid circle from theexpected position in the grid Expected X X coordinate of expectedposition of the circle in the grid. Expected position in the grid iscomputed fitting least square lines to circle centers in every row andcolumn Expected Y Y coordinate of expected position of the circle in thegrid. Expected position in the grid is computed fitting least squarelines to circle centers in every row and column CM-X X coordinate of thecenter of the mass of spot's signal region CM-Y Y coordinate of thecenter of the mass of spot's signal region CM Offset Offset (in pixels)of the spot's center of the mass from the expected position in the gridCM Offset-X X offset (in pixels) of the spot's center of the mass fromthe expected position in the grid CM Offset-Y Y offset (in pixels) ofthe spot's center of the mass from the expected position in the grid MinDiam Diameter of the circle inscribed into the spot's signal region MaxDiam Diameter of the circle, the spot's signal region can be inscribedin Control Name of a control type for current spot (no name means thespot is not a control spot) Failed Control 0 if the control passed alltests, 1 if at least one of the tests failed Background 0 if the spotpassed background contamination test, 1 if it did not ContaminationPresent Signal Contamination 0 if the spot passed signal contaminationtest, 1 if it did not Present Ignored % failed 0 if the spot passedignored percentage test, 1 if it did not Open Perimeter Failed 0 if thespot open perimeter test, 1 if it did not Shape Regularity 0 if the spotpassed shape regularity test, 1 if it did not Failed Perim-To-Area 0 ifthe spot passed perimeter-to-area test, 1 if it did not (see section1.4) Offset failed 0 if the spot passed offset test, 1 if it did notEmpty spot 1 if the spot was qualified as empty, 0 if it was notNegative spot 1 if the spot was qualified as negative, 0 if it was not

Referring now to FIG. 9, a block diagram is shown illustrating anexample of an image data analysis method 150 of the present invention.At step 151, each of the spots in the microarray are measured and themean value of each spot is calculated using the measurement module. Themodeling module is then called at step 153 to calculate thickness of thebiolayer. The kinetic course of each spot is then calculated and plottedat step 155. Spot identification information is called at step 157 andimage output tables and graphics are displayed in real-time and overtime at step 159.

Referring back to FIG. 3, output from data analysis application 82, suchas text files, XML files, or other appropriately formatted data, is sentvia line 84 to data display application 85 which further processes thedata for display. Data display application 85 includes commerciallyavailable database and spreadsheet programs such as Microsoft Access andMicrosoft Excel which can receive data from data analysis application 82and can then be manipulated by an algorithm for graphical representationof the data.

FIG. 10 is a flowchart of an example of an image data display method160. The value of a spot is first calculated by subtracting a backgroundvalue from the signal (step 161). The coordinates of the spot areretrieved, based upon quadrant A-D, row 1-12, and column 1-16 (step163). Next, a color is generated according to a range such that changeof spot) is easily visible to the user (step 165). In one example, ifthe spot value is 8-bits, the image data display method of FIG. 10assigns a gray scale value to every number between 0 and 4,096. If thespot value is 16-bits, a gray scale value is assigned to every numberbetween 0 and 65,000. At the final step 167, the method inverts the ycoordinate values for redisplay based on the viewer's perspective sincethe image view is from below the microarray in this example.

Table 2 below shows an example of software code for displayingtime-resolved values of the ellipsometric z shift data, which isproportional to film thickness change, according to the methodillustrated by the flowchart in FIG. 10.

TABLE 2  1: <%  2: Set Connl = Server.CreateObject(“ADODB.Connection”) 3: MdbFilePath = Server.MapPath(“../private/maven.mdb”)  4: Connl.Open“Driver={Microsoft Access Driver (*.mdb)}; DBQ=” & MdbFilePath & “;”  5: 6: Set diff = Conn1.Execute(“SELECT value FROM diff”& Request(“n”)&“ORDER BY field,row,column”)  7: %>  8:  9: <%  10:  11: FunctionGenerateColor(NumberToConvert, MinValue, MaxValue)  12:  13: IfNumberToConvert <= MinValue Then  14: GenerateColor = “#000000”  15:Exit Function  16: End If  17:  18: If NumberToConvert >= MaxValue Then 19: GenerateColor = “ftffffff”  20: Exit Function  21: End If  22:  23:Numerator = NumberToConvert − MinValue  24: Denominator = MaxValue −MinValue  25:  26: ScaledValue = Round(((Numerator * 255) /Denominator), 0)  27: GenerateColor = lCase(“#” & Right(“0” &Hex(ScaledValue), 2) & Right(“O” & Hex(ScaledValue), 2) & RightC‘O” &Hex(ScaledValue), 2))  28:  29: End Function  30:  31: %>  32: <html> 33: <head>  34: <title>Maven</title>  35: </head>  36: <bodybgcolor=“#000000”>  37:  38: <table cellspacing=“0” cellpadding=“0”border=“0” width=“100%” height=“100%”>  39: <tr><td align=“center”>  40: 41: <!-- main start -->  42: <table cellspacing=“0” cellpadding=“10”border=“0”>  43: <tr><td>  44:  45: <!-- 1 start -->  46:  47:  48:<table cellspacing=“20”>  49: <%  50: For Quadrant = 1 to 4  51: SelectCase Quadrant  52: Case 1: QuadrantLetter = “C”  53: Case 2:QuadrantLetter = “D”  54: Case 3: QuadrantLetter = “A”  55: Case 4:QuadrantLetter = “B”  56: End Select  57: %>  58: <%If Quadrant Mod 2=1Then%><tr><%End If%>  59: <td>  60:  61: <table cellspacing=“4”cellpadding=“0” border=“0”>  62:  63: <%  64: Set diff =Connl.Execute(“SELECT value FROM diff”& Request(“n”) &“ WHERE Field = ‘”& QuadrantLetter & “‘ ORDER BY row,column”)  65: For Row = 1 To 12  66:%>  67: <tr>  68: <%  69: For Column = 1 To 16  70: %>  71:  72: <%  73:‘ ranges for different slides  74: ‘ slide # = min,max  75: ‘00 = 0,0 76: ‘01= 4320,4900  77: ‘02 = 2660,3060  78: ‘03 = 10550,11000  79: ‘04= 6220,6700  80: ‘05 = 1520,2200  81: ‘06 = 1240,1900  82: ‘07 = 60,500 83: ‘08 = 1630,2200  84: ‘09 = 90,700  85: ‘10 = 70,650  86: ‘11 =90,650  87: ‘12 = 100,800  88: ‘13 = 3260,3900  89: ‘14 = 10890,11700 90: ‘15 = 7620,8500  91: ‘16 = 9630,10500  92: ‘17 = 12450,13500  93:‘18 = 5970,6950  94: ‘19 = 7730,8920  95: ‘20 = 8490,9500  96: ‘21 =8500,9500  97: ‘22 = 2580,3550  98: ‘23 = 10050,11000  99: ‘24 =8000,8700 100: ‘25 = 6120,6720 101: ‘26 = 6360,7100 102: ‘27 = 6050,6800103: ‘28 = 2600,3200 104: ‘29 = 6920,7500 105: %> 106: <tdbgcolor=“<%=GenerateColor(diff(“value”),2600,3200}%>”><imgsrc=“cover.gif” width=“15” height=“15” alt=“”></td> 107: <% 108:diff.MoveNext 109: Next 110: %> 111: <% 112: Next 113: %> 114: </tr>115: 116: 117: </table> 118: 119: </td> 120: <%If Quadrant Mod 2=0Then%></tr><%End If%> 121: <% 122: Next 123: Set diff = Nothing 124: %>125: </table> 126: 127: 128: </td></tr> 129: </table> 130: <!-- main end--> 131: 132: </td></tr> 133: </table> 134: 135: </body> 136: </html>137: 138: <% 139: Set diff = Nothing 140: Connl.Close 141: Set Connl =Nothing 142: %>

FIG. 11 is a block diagram of the coordinate inversion of an image slidenoted above with respect to FIG. 10.

FIG. 12 is a block diagram of an example of outputs from data displayapplication 85 which can be sent via lines 86 and/or 88 to browser 87and display device 89, respectively. Outputs include but are not limitedto real-time (live) displays, text files, and binary image files (x, y,and z values from IGOR). Real-time displays can include but are notlimited to an initial image, a current image, a differential image, athickness “map” which shows thickness over the microarray, spot“meters”, and a plot of thickness versus time. Text files can includebut are not limited to spot information and related affinityinformation.

FIG. 13 is a graph of specimen spot intensity over time in seconds.Positive and negative controls are utilized to normalize the measureddata as mentioned above. The graph demonstrates a steeper affinityslope, indicating fast interaction and more change, at the end of 75minutes in the positive control 171 than in the other specimen spots,sample 173, and negative control 175. Correlation with labelled andconventionally scanned data is also demonstrated.

FIG. 14 is an example of an html display of a frame of time-resolvedspecimen spot intensity. In one example, each frame constitutes 78kilobytes rather than the typical 600 kilobytes to 30 megabytes of thedifferential image. The data economy is thus demonstrated.

It will be apparent that FIGS. 13 and 14 are just two of a variety ofgraphical representations of the time-resolved image data which can beprovided. In one example, time-resolved image data could be displayed invarious tables, graphs, and charts.

For example, FIGS. 15-17 illustrate graphical representations of imagesubtraction, specifically subtraction of a reference image (FIG. 15)from each subsequent image (FIG. 16) in a time-resolved sequence ofimages, resulting in a “differential image” (FIG. 17) that may increasethe practical sensitivity and dynamic range of the resultant image upondigitization. For example, if measurements can be made to sevensignificant digits, and a surface is monitored over time for smallchanges, but the surface already has irregularities such as grossfeatures, roughness, or a tilt, much of the range of the resultantdigitized image will be occupied by the “background” and not the data.16-bit TIFF images are currently the most common and practical formatfor scientific imaging and analysis, due to dynamic range of thedetection methods used to create them and the data storageconsiderations of larger bit-depth images. With 65,500 levels per pixel,if the roughness and tilt remain in the image, the small surface changesof interest will comprise only a tiny range within the image, andcomparison to the reference image will reveal no discernable changes.However, if the differential image is generated before conversion to animage format such as a 16-bit TIFF, the full bit-depth of the imageformat is utilized for just the data of interest, rather than thebackground.

In FIGS. 15 and 16, a surface is measured at two different times,producing an initial and subsequent binary image. The initial image issubtracted from the subsequent image, producing the differential imagein FIG. 17. All three images are then digitized into 16-bit TIFFs byidentical means. A region of interest of the initial, subsequent, anddifferential TIFF images is displayed and analyzed. As can be easilyseen in FIG. 17, a differential image of areas 181 and 182 show a changein the areas whereas a change is difficult to notice when visuallycomparing the individual binary images of FIGS. 15 and 16.

Referring now to FIGS. 18 and 19, the initial and subsequent images havea 10,000 count range, containing 40 distinct levels, while thedifferential image covers a 25,000 count range with 112 levels. Thechanges would be undetectable if comparing the post-digitization TIFFimages.

Advantageously, the present invention allows for clear visualization ofexperimental progress in a microarray containing a plurality of specimenspots. A user interface with display device 89 is also within the scopeof the present invention such that information regarding the graphicalrepresentations may be provided to the user at his request. For example,if the user were to position a pointer at a certain area of thegraphical representation, actual data regarding the microarray, such asX and Y coordinates, thickness value, and gene ID of that sensing spot,could be displayed for the user.

The present invention also allows for ease of communication of amicroarray's experimental progress outside of the laboratory to aplurality of parties. It is apparent that the present invention is notlimited to displaying data on a single display device 89 (FIG. 3) butmay be used to display data on a plurality of display devices usingbrowser 87. Advantageously, such communication of the real-time andtime-resolved image data allows for enhanced collaboration betweenresearchers on experiments in a real-time setting. The data stream issmaller than would be required to transmit the images, which are atleast 600 kilobytes.

The above-described embodiments of the present invention are merelymeant to be illustrative and not limiting. It will thus be obvious tothose skilled in the art that various changes and modifications may bemade without departing from this invention in its broader aspects. Forexample, while communication channels within the figures, for exampleFIG. 3, have been referred to as lines, it should be understood thatwhat are called lines can be buses capable of carrying a plurality ofsignals (either digital or analog as appropriate) in parallel or caneven be wireless communication channels. Furthermore, although referenceis made to biochips in the examples above, the procedure and the resultsapply generally to chemically sensitive materials on a light reflectionsurface. Therefore, the appended claims encompass all such changes andmodifications as falling within the true spirit and scope of thisinvention.

1. An image processor, comprising: a data acquisition applicationadapted to receive spatially distributed polarization change data causedby a specimen array; and a data analyzer operably coupled to the dataacquisition application, the data analyzer adapted to calculate at leastone time-resolved value of the spatially distributed polarization changedata.
 2. The processor of claim 1, wherein the at least onetime-resolved value includes an intensity value of a specimen spot inthe specimen array.
 3. The processor of claim 2, wherein the dataanalyzer associates a color value to the intensity value.
 4. Theprocessor of claim 1, wherein the at least one time-resolved valueincludes a thickness value of a specimen spot in the specimen array. 5.The processor of claim 1, wherein the at least one time-resolved valueincludes an intensity value differential of a specimen spot in thespecimen array.
 6. The processor of claim 1, further comprising adisplay device operably coupled to the data analyzer for displaying theat least one time-resolved value in real-time.
 7. The processor of claim1, further comprising a display device operably coupled to the dataanalyzer for providing a two-dimensional representation of the spatiallydistributed polarization change occurring in the specimen array inreal-time.
 8. The processor of claim 1, further comprising a browserapplication operably coupled between the data analyzer and a network,the browser adapted to upload the at least one time-resolved value tothe network.
 9. The processor of claim 1, further comprising a userinterface operably coupled to the data analyzer for input of parametersinto the data analyzer.
 10. A method of processing image data,comprising: receiving spatially distributed polarization change datacaused by a specimen array; and calculating at least one time-resolvedvalue of the spatially distributed polarization change data.
 11. Themethod of claim 10, wherein the at least one time-resolved valueincludes an intensity value of a specimen spot in the specimen array.12. The method of claim 11, further comprising associating a color valueto the calculated intensity value.
 13. The method of claim 10, whereinthe at least one time-resolved value includes a thickness value of aspecimen spot in the specimen array.
 14. The method of claim 10, whereinthe at least one time-resolved value includes an intensity valuedifferential of a specimen spot in the specimen array.
 15. The method ofclaim 10, further comprising displaying the at least one time-resolvedvalue in real-time.
 16. The method of claim 10, further comprisingdisplaying a two-dimensional representation of the spatially distributedpolarization change occurring in the specimen array.
 17. The method ofclaim 10, further comprising uploading the at least one time-resolvedvalue to a network.